Nanoparticles are ubiquitous and by far the most abundant particle-like entities in natural environments on Earth and are widespread across many applications associated with human activities. There are many types of naturally occurring nanoparticles and man-made (engineered) nanoparticles. Nanoparticles occur in air, aquatic environments, rain water, drinking water, biofluids, pharmaceuticals, drug delivery and therapeutic products, and in a broad range of many industrial products. Nanoparticles usually occur within polydisperse assemblages, which are characterized by co-occurrence of differently-sized particles.
Nanoparticles are (as per ISO definition) particles smaller than 100 nm in diameter (more precisely, each of three Cartesian dimensions is smaller than 100 nm). However, in practical applications, this range has been extended into sub-micron or smaller than 1000 nm diameters. The latter is sometimes called mesoscale.
Given the widespread usage of nanoparticles, the ability to control and accurately characterize their properties may be useful to many applications. Conventional methods for measuring nanoparticle properties include Nanoparticle Tracking Analysis, which uses a microscope and video camera to analyze frames of the recorded videos to track images of light reflected or scattered by the nanoparticles undergoing Brownian motion.
Analysis of Brownian motion of nanoparticles allows for their sizing as described by A. Einstein (1905 Annalen der Physik 17 pp. 549-560) and is based on the simple assumption that such particles are more or less spherical, which means that their random movements are equally probable in all directions. Currently laser light sources with suitable optics are used, which allow for the creation of a very narrow light sheet, and the light scattering off the nanoparticles is observed at a right angle. This is called dark field microscopy. This type of microscopy, however, assumes that the nanoparticles can continuously scatter light, thus creating images with stable intensity (not changing much in time) to allow for uninterrupted tracking of particles' movements by the software. Both above mentioned assumptions (spherical and continuous light scattering) are frequently not possible. The most obvious example is that highly elongated particles like tobacco mosaic viruses (TMVs) look like rods with a diameter of about 20 nm and a length of about 300 nm, having a surface resembling a corn cob, as witnessed by TEM images, cf. e.g. P. Ge and Z. H. Zhou 2011 PNAS 108(23), pp. 9637-0642.
For such highly elongated and rough surface particles, light scattering intensity varies in time and depends heavily on the orientation of a given particle with respect to the light sheet (different effective cross-sections) and the particle's rotation. In practical terms, images recorded for such particles show characteristic blinking with frequencies of several Hz, while their Brownian translational motion can be separated into two completely different movements, with the Brownian rotation enhancing blinking, a la a disco ball effect (a rotating surface covered with flat mirrors that sheds pulses of light scattered into various directions).
When current instrumentation for sizing nanoparticles by Brownian motion tracking encounters such particles, the instrumentation has severe problems that limit or completely inhibit accurate sizing. The instrumentation observes incomplete nanoparticle tracks that are too short for accurate sizing and are impossible to correct by connecting tracks across multiple video frames when recording videos at standard 30 fps.
Therefore, there exists a need for a system and method that addresses the blinking of a nanoparticles and accounts for nanoparticles that might be elongated, when processing the images, to arrive at a particle size based on Brownian motion.